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Assessment of mechanical properties of isolated bovine intervertebral discs from multi-parametric magnetic resonance imaging

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imaging

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Maximilien Recuerda, Delphine Périé-Curnier, Guillaume Gilbert et

Gilles Beaudoin

Date: 2012

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Article de revue / Journal article

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:

Recuerda, M., Périé-Curnier, D., Gilbert, G. & Beaudoin, G. (2012). Assessment of mechanical properties of isolated bovine intervertebral discs from

multi-parametric magnetic resonance imaging. BMC Musculoskeletal Disorders, 13. doi:10.1186/1471-2474-13-195

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Journal Title: BMC Musculoskeletal Disorders (vol. 13)

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R E S E A R C H A R T I C L E

Open Access

Assessment of mechanical properties of isolated

bovine intervertebral discs from multi-parametric

magnetic resonance imaging

Maximilien Recuerda

1,2

, Delphine Périé

1,2*

, Guillaume Gilbert

3

and Gilles Beaudoin

4

Abstract

Background: The treatment planning of spine pathologies requires information on the rigidity and permeability of the intervertebral discs (IVDs). Magnetic resonance imaging (MRI) offers great potential as a sensitive and

non-invasive technique for describing the mechanical properties of IVDs. However, the literature reported small correlation coefficients between mechanical properties and MRI parameters. Our hypothesis is that the compressive modulus and the permeability of the IVD can be predicted by a linear combination of MRI parameters.

Methods: Sixty IVDs were harvested from bovine tails, and randomly separated in four groups (in-situ, digested-6h, digested-18h, digested-24h). Multi-parametric MRI acquisitions were used to quantify the relaxation times T1 and T2, the magnetization transfer ratio MTR, the apparent diffusion coefficient ADC and the fractional anisotropy FA. Unconfined compression, confined compression and direct permeability measurements were performed to quantify the compressive moduli and the hydraulic permeabilities. Differences between groups were evaluated from a one way ANOVA. Multi linear regressions were performed between dependent mechanical properties and independent MRI parameters to verify our hypothesis. A principal component analysis was used to convert the set of possibly correlated variables into a set of linearly uncorrelated variables. Agglomerative Hierarchical Clustering was performed on the 3 principal components.

Results: Multilinear regressions showed that 45 to 80% of the Young’s modulus E, the aggregate modulus in absence of deformation HA0, the radial permeability krand the axial permeability in absence of deformation k0can be explained by the MRI parameters within both the nucleus pulposus and the annulus pulposus. The principal component analysis reduced our variables to two principal components with a cumulative variability of 52-65%, which increased to 70-82% when considering the third principal component. The dendograms showed a natural division into four clusters for the nucleus pulposus and into three or four clusters for the annulus fibrosus. Conclusions: The compressive moduli and the permeabilities of isolated IVDs can be assessed mostly by MT and diffusion sequences. However, the relationships have to be improved with the inclusion of MRI parameters more sensitive to IVD degeneration. Before the use of this technique to quantify the mechanical properties of IVDs in vivo on patients suffering from various diseases, the relationships have to be defined for each degeneration state of the tissue that mimics the pathology. Our MRI protocol associated to principal component analysis and agglomerative hierarchical clustering are promising tools to classify the degenerated intervertebral discs and further find

biomarkers and predictive factors of the evolution of the pathologies.

Keywords: Intervertebral disc, Compression tests, Mechanical properties, Multi-parametric MRI, Multiple linear regressions

* Correspondence:delphine.perie@polymtl.ca

1

Mechanical Engineering Department, Ecole Polytechnique de Montréal, Montréal, QC, Canada

2

Research Center, CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada

Full list of author information is available at the end of the article

© 2012 Recuerda et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Background

The planning of the treatment of spine pathologies requires information on the rigidity of the tissues. The surgeons use side-bending radiographs to estimate the rigidity of the spine, but the results vary with the muscular effort made by the patient [1,2]. A fulcrum bending test was developed to more accurately reflect the spine flexibility [3] as well as a suspension test [4]. Reverse methods including a finite element model of the spine have been developed but the segmentation process of the radiographs and the inversion of the reverse problem are computationally challenging. Consequently, these methods are not clinically used on a regular basis, and the information remains global.

The intervertebral disc (IVD) plays an important role in the mobility of the vertebral segments. As IVDs de-generate, the nucleus pulposus becomes more consoli-dated and fibrous, and is less clearly demarcated from the annulus fibrosus in which focal defects appear and there is a decrease in the number of layers [5,6]. The mechanical behaviours of the IVD matrix and their changes with degeneration have been widely investigated on nonviable tissue in vitro, with reported loss of disc height, fluid pressurization and hydration, and altered compressive modulus, shear modulus, or permeability [7-11]. Thus it is important to be able to quantify the compressive modulus of the IVD to assess the spine ri-gidity. Moreover, the IVD is an avascular tissue, except in the outermost annulus fibrosus, and its nutrition is achieved by diffusion from the vertebral endplates [12]. A reduced permeability of the disc will decrease the nu-trition of the inner AF and nucleus pulposus, and increases their degeneration. Thus it is important to be able to quantify the permeability of the IVD. Moreover, the permeability may vary between the endplates border of the healthy disc, where there is the diffusion of the nutriments and the periphery of the annulus fibrosus. However, we only know the changes in the zero-strain permeability from the nucleus pulposus (0.68±0.09* 10-15m4N-1s-1) to the annulus fibrosus (0.24±0.19*10-15 m4N-1s-1) as computed from confined compression tests and non linear biphasic models, with no differentiation between inner and outer annulus fibrosus [10,13].

Multi-parametric MRI has been investigated as an early diagnostic tool of IVD degeneration by correlat-ing the MRI parameters to the IVD degeneration. IVD water, proteoglycan and collagen contents were found to be correlated to the longitudinal relaxation time (T1), the transverse relaxation time (T2), the time constant of the exponential decay of magnetization during a spin-lock radiofrequency pulse (T1ρ), the magnetization transfer ratio (MTR) and the diffusion [14-17]. T1 and T2 decreased when the Thompson grade increased in the nucleus pulposus [16,18,19]. Magnetization transfer (MT) sequence was sensitive to Thompson grades

in in-vivo studies [18] and slightly to Pfirrmann grades [20]. Furthermore changes in the extracellular matrix structure and fiber organization altered the MTR [16]. The appar-ent diffusion coefficiappar-ent (ADC) decreased with increasing Thompson grades and also with increasing loading of the IVD [19,21]. Antoniou et al. [17] showed that the ADC in the nucleus pulposus decreased with a decrease in proteo-glycan and water contents. These decreased ADC values reflected the lost integrity of the intervertebral [22].

As a result of these correlations between the MRI parameters and the biochemical properties and between the biochemical properties and the mechanical proper-ties [9,23], multi-parametric MRI was used to estimate the mechanical properties of IVD tissues. The hydraulic permeability and T1 were found to be correlated in cau-dal bovine nucleus pulposus [11]. Weak linear correl-ation was found between T1ρ and the osmotic pressure of the human nucleus pulposus [24]. On bovine discs, strong relationships were found between permeability and MRI parameters including T1ρ in the nucleus pul-posus and correlations were found between axial perme-ability and T1ρ in the annulus fibrosus and between compressive modulus and T1ρ in the nucleus pulposus [25]. T2 and permeability were correlated in bovine nucleus pulposus and the only mechanical property associated to the MR diffusion was the permeability, and a trend was found between ADC and HA0 [26]. MRI scaling using Gibson’s scale on T2-weighted MRI images was able to categorize the elastic modulus and the viscosity of the IVDs in two clearly distinct groups with-out overlaps according to degeneration [27]. MRI offers great potential as a sensitive and non-invasive technique for describing the alterations in mechanical properties of IVDs. However, the literature showed large standard deviations in the determination of the mechanical prop-erties of the IVD and small coefficients of correlation be-tween mechanical properties and MRI parameters. The assessment of the permeability value was usually done by mathematical model regression, but it can be esti-mated more accurately by direct measurement using a custom setup according to the Darcy theory [28-30].

Our hypothesis is that the compressive modulus and the hydraulic permeability of the IVD can be predicted by a combination of MRI parameters (T1, T2, MTR, ADC, fractional anisotropy FA). Our specific aim is to measure the mechanical properties, using confined and unconfined compression tests and direct permeability measurements, and the MRI parameters of isolated bo-vine IVDs and to investigate the relationships between these parameters. Bovine caudal IVDs from 6 months old animals are usually healthy. Thus, to validate the use of multi-parametric MRI to evaluate the mechanical properties of degenerated IVDs, we digested the bovine IVDs. Trypsin is known to decrease the Young’s

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modulus, increase the permeability and alter the struc-ture of the disc [11,23].

Methods

Samples preparation

Bovine tails were obtained from a local slaughterhouse within 4 hours of death. The skin, muscles, ligaments and vertebrae pedicles were removed from each tail. Transverse cuts were performed along the cartilaginous endplates to isolate the two proximal discs. Sixty discs with a controlled 15mm thickness were randomly sepa-rated in four groups. The discs from the in-situ group (n=15) were wrapped in plastic to prevent dehydration. The discs from each of the 4 digested groups (n=15 per group) were digested in PBS solution with a specific concentration of trypsin from bovine pancreas (T8003 Sigma-Aldrich), during a varying amount of time at 37° with shaking. The duration of the digestion and the con-centration of the trypsin are summarized in Table 1. Trypsin, a mammalian serine protease, catalyzes the hy-drolysis of peptide bonds at the carboxyl side of lysyl and arginyl residues. Trypsin was chosen to induce gen-eral degradation of the disc structure and composition. A light platen of plastic was placed on the top of the disc to avoid bulging during the treatment. Their wet weights were measured before and after digestion to quantify the percentage of hydration.

MR imaging

Immediately after digestion, samples were removed from the shaking water bath, and were gently blotted to re-move absorbed water. Thickness and weight of discs from both groups (digested and in-situ) were measured just before the MRI acquisition. Discs were placed in chambers filled with PBS solution. A light platen was placed on the top to stabilize the discs during the MRI acquisition. The acquisition was performed using a 3T whole-body system (Philips Achieva X-Series). Images for the quantification of T1 (Figure 1-a) and T2 (Figure 1-b) were acquired using a multiple inversion recovery turbo spin-echo (TSE) sequence for T1 (TR/ TE=2100/6.3ms, 15 inversions times (TI) from 50 to 1900ms) and a multi-echo turbo spin-echo (TSE) se-quence for T2 (TR=2000ms, 10 TE every 15ms). T1 and T2 were extracted (Matlab, r2007 Mathworks, Natick, MA) from the signal intensity (SI) by fitting equations 1 and 2 [31]. SITI¼ S0 1 1  cos αð ð ÞÞETI 1 ETWf N 1 ETE=2 2       ð1Þ with f xð Þ ¼ 1  ETEx; ETI¼ e TI T1; ETW ¼ eTWT1; ETE ¼ eTET1 and N=8. SITE ¼ SIðTE¼0ÞeTE=T2 ð2Þ

Where SI is the signal intensity, α the refocusing angle =180º, TW the time in ms between the last re-focusing pulse and the next inversion pulse, and N the number of refocusing pulses.

The MTR was obtained using two gradient echo sequences (TR/TE=83/3.8 ms, single off-resonance sinc-gauss pulse, 19.25 ms duration, 620 degrees effective flip angle), one with the off-resonance pulse applied at 1100Hz down to the free water proton resonance fre-quency (Ms, Figure 1-c) and the other one without it (Mo, Figure 1-d) [20]. MT ratio was calculated from equation 3 [32].

MTR¼M0 MS

M0 ð3Þ

The last sequence measured the ADC and FA using a spin-echo EPI diffusion-weighted sequence (TR/TE=2000/ 40 ms) with 15 non-collinear diffusion and a b value of 1000 s/mm2 (Figure 1-e). ADC and FA were calculated using equations 4, 5, 6 [33-35]: SIð Þb ¼ SIðb¼0Þeb:D ð4Þ ADC¼λ1þ λ2þ λ3 3 ð5Þ FA¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 3 ðλ1 ADCÞ2þ λð 2 ADCÞ2þ λð 3 ADCÞ2

 

2λ21þ λ22þ λ23 s

ð6Þ Where b is the diffusion encoding tensor, D the diffu-sion tensor andλ the eigenvalues of D.

Each MR image was semi-automatically segmented using Slice-O-Matic (Tomovision, Magog, Canada). A manual selection of 8 points on the exterior outline of the IVD and nucleus pulposus allowed the contour to be approximated by the Snake algorithm. A manual correc-tion of each contour was then realized to improve their anterior and posterior extremities. The annulus fibrosus zone was obtained by the subtraction of the nucleus pul-posus zone from the IVD zone. The repetition of the semi-automatic segmentation by a same operator and the skills of the operator did not influence the quality of the contour (p=0.8-1.0) while the instructions given prior to the segmentation influenced the quality of the contour (p<0.05).

Table 1 Trypsin digestion groups

Group Duration Concentration [mg/ml]

Digested-6h 6h 0.05

Digested-18h 18h 0.1

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Mechanical testing

Just after the MRI acquisitions, all discs were frozen (−80°C) until the day of mechanical testing to avoid any additional enzyme degradation or dehydration of the tissue. It is recognized that freezing does not affect the determination of the mechanical properties of IVDs and it facilitates the preparation of the tissue [25,26]. Three mechanical tests were performed: unconfined and con-fined compression tests and direct permeability meas-urement. IVDs were punched with a 5mm diameter punch in both the nucleus pulposus and posterior annu-lus fibrosus regions. Each punched sample was divided into four slices of height 1.6±0.5mm, three slices being tested mechanically and one being reserved for bio-chemical measurements. The protocols for confined and

unconfined compression tests of IVDs were based on previous studies in which we identified the initial testing conditions allowing the highest reproducibility of the measures. In unconfined compression, the protocol in-cluding an initial swelling, a 5% strain preload and a 5% strain ramp is the most relevant protocol to test the an-nulus fibrosus while the protocol with semi confined swelling and a 5% strain ramp is the most relevant protocol for the nucleus pulposus [36]. In confined com-pression, the best initial condition was the confined swelling followed by a 5% strain ramp [13].

Unconfined compression

The unconfined compression test was performed using the mechanical testing machine Mach-1 (Biomomentum,

Figure 1 Example of T1 weighted image (a), T2 weighted image (b), MT image with the off-resonance pulse (c), MT image without the off-resonance pulse (d) and Diffusion weighted image (e) for an isolated IVD.

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Montreal, QC, Canada). Before the test, tissues were bathed during 10 minutes in PBS in free condition for the annulus fibrosus or in semi-confined condition (allowing only radial displacement) for the nucleus pul-posus. After the tissue sample was placed in the cham-ber for the unconfined compression test, the upper platen was lowered until a stable force of 8 × 10-5N for the annulus fibrosus or 6 × 10-5N for the nucleus pulpo-sus was recorded, indicating that the platen was in con-tact with the top of the specimen with no deformation of the specimen. The thickness of the tissue sample was then deduced from the relative position of the upper platen to the bottom of the chamber. A preloading of 5% strain during 10min was applied to the annulus fibrosus. Five successive stress-relaxation ramps were applied using 5% strain increment. The relaxations were stopped when the slope of the curve reached a rate of 0.1g per min. The mechanical properties were computed (Matlab, r2007 Mathworks, Natick, MA) using a visco-elastic model [37] to evaluate the Young’s modulus or (E) and the viscocity (μ), and a linear biphasic porovis-coelastic mathematical model [38,39] to evaluate the ra-dial permeability (kr), the Poisson’s ratio (ν), and the viscoelasticity (c). The Young’s modulus or modulus of elasticity can be used to predict the elongation or com-pression of an object as long as the stress is less than the yield strength of the material. Viscosity describes a fluid’s internal resistance to flow and may be thought of as a measure of fluid friction. The hydraulic permeability indicates the resistance to fluid flow through the inter-vertebral disc matrix. The Poisson’s ratio is the ratio of transverse contraction strain to longitudinal extension

strain in the direction of stretching force. Viscoelasticity is the property of materials that exhibit both viscous and elastic characteristics when undergoing deformation, for which the relationship between stress and strain depends on time.

Confined compression

The confined compression test was performed with the same apparatus used for the unconfined compression test. A custom non porous acrylic chamber (5 milli-meters diameter) was designed and manufactured. The protocol described in previous studies [10,13] was used. However, the relaxation period was stopped when the force slope was lower than 0.1g/min. The aggregate modulus HA0and the axial hydraulic permeability k0for zero-strain and their respective nonlinear coefficients β and M were computed from a non linear biphasic model [10,40-42]. The aggregate modulus is a measure of the stiffness of the tissue at equilibrium when all fluid flow has ceased. The higher the aggregate modulus, the less the tissue deforms under a given load.

Permeability measurement

The apparatus used to measure the axial permeability consisted of a cylindrical acrylic chamber (Figure 2). Two filters (diameter: 5mm, pore size: 60μm) allowed a fluid to circulate through the tissue sample. The up-per filter was fixed to the actuator controlled elec-tronically by the mechanical testing machine (Mach-1, Biomomentum, Montreal, QC, Canada). The fluid flow was regulated by a syringe pump (Cole Parmer, Vernon Hills, IL) using a 500μl Hamilton syringe and the flow

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pressure inside the system was measured by a 15psi gauge pressure. The outside pressure was the atmos-pheric pressure. The system was filled with PBS, the sample was introduced carefully in its chamber and the thickness was immediately measured with a tare load of 1g. The contact was maintained for 1h to obtain the stress equilibrium. The reacting force was continuously monitored. The fluid was injected from the syringe pump at a high rate (400μl/h) until a pressure difference across the sample of 40±0.5kPa was recorded. A low fluid rate was then injected (in a range of 20-25μl/h) and the fluid flow was manually adjusted until the equilib-rium was reached, for a slope rate lower than 0.01g/min during a 5 min period. The hydraulic permeability (ka) was calculated from the Darcy law: for a laminar fluid flow with a low Reynolds number, the intrinsic perme-ability k (m4/Ns) of a saturated porous sample is derived from Equation 7 where Q (m3/s) is the flow rate, ΔP (Pa) is the pressure difference,μ (Ns/m2) is the fluid dy-namic viscosity, l (m) is the length of the sample and S (m2) is the cross-section of the sample [43,44].

k¼ Qlμ

ΔPS ð7Þ

Statistical analyses

Only the compressive modulus and the permeabilities were chosen for the statistical tests as they presented the smallest standard deviation per group and represent the most important mechanical properties of a biphasic ma-terial. For each mechanical property or MRI parameter, a one way ANOVA was performed on the 4 groups fol-lowed by a post-hoc multiple comparison with the Dunn-Sidak method. Multi linear regressions were per-formed between dependent (E, kr, HA0, k0 and ka) and independent (T1, T2, MT, FA and ADC) variables to verify our hypothesis.

However, the MR parameters might be found depend-ant. Thus, a principal component analysis was used to convert the set of possibly correlated variables into a set of linearly uncorrelated variables. The data were first centered and reduced, and organized as a matrix where each row represents a different observation of the ex-periment and each column gives a different mechanical or MR parameter. The covariance matrix and its eigen-vectors and eigenvalues were computed. The cumulative energy content for each eigenvector was used to select a subset of eigenvectors as basis vectors. The source data were then converted into the new basis. The first princi-pal component (F1) has the largest possible variance, and each succeeding component (F2, F3, . . .Fn) in turn has the highest variance possible under the constraint that it is orthogonal to the preceding components.

Agglomerative Hierarchical Clustering was performed on the 3 first principal components (F1, F2 and F3) computed from the mechanical properties or the MRI parameters. Each observation was a cluster and the process successively merged clusters into larger clusters until it reached one big cluster containing all the sam-ples. We used the Euclidian distance to determine a pairwise distance metric between each observation. The merging of clusters, or linkage, was based on the calcula-tion of the Ward’s distance between clusters. Ward’s linkage uses the incremental sum of squares; that is, the increase in the total within-cluster sum of squares as a result of joining two clusters. The within-cluster sum of squares is defined as the sum of the squares of the dis-tances between all objects in the cluster and the centroid of the cluster. These successive clustering operations produced a binary clustering tree (dendrogram), whose roots contained all the observations.

All statistical tests were performed using XLSTATS (Addinsoft, New York, United States). All results were expressed as Mean±SD and the significance of all tests was set to p≤0.05.

Results

The enzyme treatment induced mechanical changes in both the annulus fibrosus and nucleus pulposus, with a decrease of the compressive moduli and an increase of the permeabilities (Table 2). For both the annulus fibro-sus and nucleus pulpofibro-sus, ADC decreased while FA increased between in-situ and digested groups while there were no changes on T1, T2, and MT (Table 3). The one-way ANOVA confirmed significant differences on the compressive modulus between in-situ and digested groups, but not between the digested groups, and on the ra-dial permeability between the digested groups and between the in-situ and digested 24h groups (Table 4). Significant differences were found on the axial permeabilities between

Table 2 Young’s modulus E (MPa), compressive modulus HA0(MPa), permeabilities kr, k0and ka(e-15m4/Ns)

presented as mean ± SD for all groups (n=15 per group)

E kr HA0 k0 ka Nucleus pulposus In-situ 0.019±0.017 32±27 0.12±0.08 15±17 10±2 Dig 6h 0.008±0.007 74±40 0.04±0.04 31±15 13±3 Dig 18h 0.012±0.015 111±154 0.03±0.03 26±19 14±2 Dig 24h 0.007±0.008 218±210 0.02±0.01 40±22 16±3 Annulus fibrosus In-situ 0.035±0.030 11±8 0.22±0.17 20±27 8±4 Dig 6h 0.029±0.019 12±17 0.09±0.06 11±16 7±2 Dig 18h 0.023±0.018 21±16 0.04±0.03 37±28 7±2 Dig 24h 0.012±0.013 59±58 0.07±0.06 9±8 9±2

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the in-situ and digested groups, but only for the nucleus pulposus. No significant differences were found on T1 and MTR between all groups. Significant differences were found on T2 for the annulus fibrosus, on ADC for the nucleus pulposus and on FA for both annulus fibrosus and nucleus pulposus.

Multi linear regressions showed that 52 to 70% of E and HA0can be explained by the MRI parameters within the annulus fibrosus, except for E within the digested 6h group and for HA0 within the in-situ group (Table 5). Within the nucleus pulposus, 45 to 68% of E and HA0 can be explained by the MRI parameters, except for HA0 within the digested 6h and digested 24h groups. 52 to

80% of the radial permeability kr can be explained by the MRI parameters for both annulus fibrosus and nucleus pulposus, except for the annulus fibrosus with-in the with-in-situ group. 32 to 65% of the axial permeability in absence of deformation k0 and 41 to 70% of the axial permeability ka can be explained by the MRI parameters.

The linear regressions found for each mechanical property included all the MRI parameters measured in this study (Equation 8). The variance inflation factor (VIF) of T1 and T2 was always higher than the VIF of MT, ADC and FA, suggesting that these parameters were likely candidates for elimination in the equation. However, after removing T2 that presented the highest VIF, all parameters had equivalent VIF and the coeffi-cient of determination did not change significantly.

MP¼ a0þ a1 T1þ a2 T2þ a3 MT

þ a4 ADCþ a5 FA ð8Þ

Where MP is one of the mechanical properties E, kr, HA0, k0and ka, and ai(i=0-5) are constants.

The principal component analysis reduced our six variables (one mechanical property E, kr, HA0, k0 or ka, and five MR parameters T1, T2, MTR, ADC and FA) to two principal components F1 and F2 with a cumulative variability of 52-65%, which increased to 70-82% when considering the third principal component F3. The rep-resentation of the six variables in the (F1, F2) plane for the nucleus pulposus (Figure 3) showed correlations be-tween T1 and T2 as they were located near the circle

Table 3 Relaxation times T1 and T2 (ms), magnetization transfer ratio MTR (x100) and diffusion parameters FA and ADC (mm2/s) presented as mean ± SD for all groups (n=15 per group) T1 T2 MTR FA.10-2 ADC.10-4 Nucleus pulposus In-situ 1140±76 124±16 34±20 8.03±4.59 15.04±0.62 Dig 6h 1056±130 87±26 28±15 18.59±6.67 15.25±1.58 Dig 18h 1115±130 123±5 33±24 8.15±4.52 14.79±1.13 Dig 24h 1144±78 118±7 32±22 13.03±7.08 14.17±0.84 Annulus fibrosus In-situ 706±44 70±11 44±15 15.83±3.05 15.89±1.06 Dig 6h 659±71 62±11 38±13 23.87±5.24 16.87±0.95 Dig 18h 663±73 65±5 42±18 17.10±4.60 15.34±1.27 Dig 24h 710±85 68±5 42±16 20.89±4.93 15.42±1.13

Table 4 p-values from the one way ANOVA performed on the 4 groups for each mechanical property or MRI parameter of the nucleus pulposus and annulus fibrosus

E kr HA0 K0 ka T1 T2 MTR ADC FA Nuclus Pulposus Global 0.09 0.002 0.0001 0.03 0.0001 0.19 0.0003 0.88 0.10 0.0002 In situ / Dig. 6h 0.07 0.53 0.0002 0.07 0.006 0.06 0.0001 0.45 0.65 0.0001 In situ / Dig. 18h 0.73 0.66 0.0001 0.2 0.0001 0.58 0.94 0.89 0.58 0.96 In situ / Dig. 24h 0.03 0.001 0.0001 0.004 0.0001 0.92 0.53 0.75 0.06 0.04 Dig. 6h / Dig. 18h 0.15 0.85 0.67 0.58 0.14 0.20 0.0002 0.54 0.32 0.0001 Dig. 6h / Dig. 24h 0.77 0.0006 0.36 0.26 0.01 0.05 0.001 0.66 0,02 0.03 Dig. 18h / Dig. 24h 0.08 0.003 0.64 0.09 0.30 0.52 0.58 0.86 0.18 0.05 Annulus Fibrosus Global 0.04 0.002 0.001 0.05 0.38 0.18 0.33 0.86 0.008 0.0004 In situ / Dig. 6h 0.52 0.84 0.005 0.40 0.43 0.12 0.009 0.40 0.04 0.0001 In situ / Dig. 18h 0.06 0.44 0.0001 0.14 0.23 0.16 0.26 0.82 0.24 0.5 In situ / Dig. 24h 0.01 0.001 0.001 0.24 0.71 0.88 0.67 0.78 0.31 0.009 Dig. 6h / Dig. 18h 0.22 0.57 0.21 0.02 0.67 0.88 0.55 0.55 0.002 0.001 Dig. 6h / Dig. 24h 0.05 0.001 0.5 0.75 0.25 0.09 0.19 0.57 0.003 0.12 Dig. 18h / Dig. 24h 0.47 0.007 0.53 0.01 0.12 0.12 0.49 0.96 0.87 0.05

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and near to each other. Their position near the X-axis suggested that F1 expressed mainly these parameters. ADC, E, ka and krwere far away from the circle, which suggested that these parameters were not expressed only by F1 or F2. The eigenvectors of the covariance matrix showed that these parameters were expressed more by F3 than F1 or F2. The representation of the six variables in the (F1, F2) plane for the annulus fibrosus (Figure 4) showed no correlations between the parameters, except for T1 and FA that were located near the circle and seems to be symmetric relatively to the circle origin. MT, FA, HA0, k0and krwere expressed more by F3 than F1 or F2.

One way to determine the natural cluster division in a dataset is to compare the height of each link in the dendogram. A link, whose height differs notice-ably from the height of the links below, indicates that the objects joined at this level are much farther apart from each other than their components were when they were joined. The dendograms obtained from the MRI parameters showed a natural division into four clusters for the nucleus pulposus but only three clus-ters for the annulus fibrosus (Figure 5). Indeed, above those four clusters for the nucleus pulposus or three clusters for the annulus fibrosus, no link differs no-ticeably from the height of the links bellow. The den-dograms obtained from the mechanical properties showed a natural division into 4 clusters for both the annulus fibrosus and nucleus pulposus (Figure 6). From the mechanical parameters of the nucleus pul-posus, the first cluster contained samples from the in-situ group, the second from the digested 18h and digested 24h groups, the third from the three digested groups and the fourth from the digested 24h group. From the mechanical properties of the annulus fibro-sus, the first cluster contained samples from the in-situ and digested 6h groups, the second from the digested 18h group, the third from the in-situ group and the fourth from the digested 24h group. From the MRI parameters of both the nucleus pulposus and annulus fibrosus, all the clusters contained sam-ples from all groups.

Discussion

Multi-parametric MRI acquisitions, unconfined and con-fined stress-relaxation tests in compression and direct permeability measurements were performed on isolated bovine IVDs, as opposed to previous studies done on bovine tail segments [14,25,26]. Isolated IVDs soaking in a trypsin solution was efficient to simulate degradation as it resulted in an increase of the hydration, a proteo-glycan decrease in the nucleus pulposus and an alter-ation of the structure in both annulus fibrosus and nucleus pulposus. However, this enzyme digestion is not representative of in vivo degeneration mainly because of the water content, which increases with enzyme diges-tion and decreases with degeneradiges-tion. However, the aim of this study was to assess the ability of multi-parametric MRI to quantify the mechanical properties of IVDs pre-senting various compressive modulus or permeabilities.

The mechanical properties were sensitive to our enzyme digestion: the compressive modulus decreased while the permeability increased, in agreement with the literature [23]. The ability of the disc tissue to withstand mechanical forces largely depends on the structural integrity of the matrix and on the biochemical contents [9,45]. The HA0 decrease is associated to both structural matrix integrity

Table 5 Coefficient of determination R2, standard error of estimate (MPa for E and HA0, e-15m4/Ns for kr, k0and ka)

and power of the performed test withα=0.05 of the multilinear regressions between the mechanical properties and the MRI parameters for the nucleus pulposus and the annulus fibrosus

Coefficient of determination R2

Standard error of estimate Power withα=0.05 E kr HA0 k0 ka Nucleus Pulposus In-situ 0.48 0.53 0.48 0.49 0.70 0.04 55.6 0.08 73.4 1.2 0.73 0.79 0.72 0.74 0.95 Digested-6h 0.48 0.62 0.34 0.45 0.67 0.007 34.6 0.06 15.6 2.2 0.67 0.85 0.47 0.63 0.90 Digested-18h 0.68 0.62 0.45 0.34 0.55 0.01 151.9 0.05 21.9 2.1 0.91 0.85 0.63 0.48 0.76 Digested-24h 0.65 0.63 0.27 0.38 0.41 0.006 173.7 0.03 24.5 3.2 0.91 0.90 0.41 0.58 0.63 Annulus Fibrosus In-situ 0.52 0.17 0.65 0.65 0.48 0.03 9.8 0.14 40.4 3.6 0.78 0.26 0.91 0.88 0.73 Digested-6h 0.15 0.52 0.49 0.39 0.45 0.02 41.7 0.06 62.5 2.1 0.21 0.73 0.72 0.49 0.63 Digested-18h 0.70 0.66 0.63 0.32 0.48 0.01 13.1 0.03 266.2 2.2 0.92 0.89 0.86 0.44 0.68 Digested-24h 0.01 0.80 0.21 0.32 0.71 0.93 35.1 0.07 34.1 1.6 0.67 0.99 0.32 0.48 0.95

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and biochemical content. The permeability, highly aniso-tropic for healthy IVDs, becomes slightly more isoaniso-tropic with degeneration. The degeneration process is associated with a change in water content and induces an increase in the pore size in the radial direction only, but no change in the porosity between collagen lamella [29]. Thus, in this

study, the changes in the permeability are dependent on the fluid flow direction, for which the collagen orientation plays an important role, and might also be due to the tissue hydration.

Trypsin digestion did not affect T1, T2 and MTR, as previously reported on bovine tails [14,25]. T1 has been

Figure 3 Principal component analysis, representation of the mechanical property (a- E, b- HA0, c- k0, d- ka, e- kr) and MRI parameters

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shown to correlate with disc water content and not with proteoglycan content. T2 has been shown to be an indi-cator for the integrity of the collagen network, and MTR is known to be correlated to the collagen structure and composition [18], and thus our digestion process seems

to have not affected the collagen structure or content. This is justified knowing that trypsin catalyzes the hy-drolysis of peptide bonds at the carboxyl side of lysyl and arginyl residues [46], and thus principally cleaves the proteoglycan core protein [14]. The most sensitive

Figure 4 Principal component analysis, representation of the mechanical property (a- E, b- HA0, c- k0, d- ka, e- kr) and MRI parameters

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MRI parameters were ADC and FA. The decrease of ADC reflects less diffusion within the tissue, which might be associated to less nutrition in vivo [12], and consequently to IVD degradation. The increase of FA reflects a structural integrity that entails a preferred dir-ection of the fluid flow within the tissue. We previously demonstrated that, while the trypsin digestion increased the anisotropy, the hydration decreased the anisotropy and thus increased the disorganization of the collagen fibers within the annulus fibrosus. Significant differences were found only between the in situ and digested 6h groups for T2. In this digested 6h group, there is the effect of the hydration and not of the enzyme digestion. We previously demonstrated that a progressive decrease of both T1 and T2 between in-situ and hydrated groups, and a progressive increase between the hydrated and digested groups were observed. The effect of proteogly-cans cleaving from trypsin digestion on the MRI relax-ation times is hidden by the effect of hydrrelax-ation. The changes in the MRI parameters are smaller than the changes in the mechanical properties. The MR relax-ation times are not the best candidates to reflect the changes in the mechanical properties. However, the dif-fusion parameters are sensitive to these changes.

The MRI parameters chosen in this study (T1, T2, MT, FA, ADC) can assess the compressive moduli and the ra-dial or axial permeability, in agreement with the literature [11,25]. However, our results suggest that the relaxation time T2 could be removed from the equations because of its high variance inflation factor. T1ρ, which is known to be more sensitive to the IVD degenerescence than T1

and T2 [14,25], would be the perfect candidate to im-prove our regressions. The expression of the multi-linear regressions between the mechanical properties and MRI parameters differs from a group to another one, for both annulus fibrosus and nucleus pulposus. The differences between the digested groups might be due to the method used to quantify the mechanical properties of the IVD. While we achieved the highest possible consistency of protocol in the mechanical testing, there were technical challenges in measuring nucleus pulposus tissues due to the extremely low stiffness and lack of geometric stability, particularly for the enzymatically treated samples. This point is illustrated by the high standard deviation found for k0. However, the direct measurement of the perme-ability reduces the standard deviations and the differences between the linear regressions. The quantification of the MR parameters is more accurate than the determination of the mechanical properties because the MRI protocol was rigorously the same for all acquisitions and the annu-lus fibrosus or nucleus pulposus segmentations were fully automatic using a Canny edge detection algorithm. The differences between the in-situ and digested groups might be due to the sensitivity of the MR parameter to a specific change in the composition or structure of the tissue. Thus, the linear regressions between the mechanical properties and MRI parameters have to be defined for each type of degeneration that mimics the pathology we want to study in vivo.

The reduction of the variables to two or three principal components confirmed that the relationships between the mechanical properties and MRI parameters may be non

Figure 5 Dendograms generated from the principal components of the MRI parameters for the nucleus pulposus (a) and the annulus fibrosus (b). The Y axis is the distance between the two objects being connected and the X axis is the node number.

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linear. Principal component analysis is very useful to re-duce the dimensionality of a data set by projecting high dimensional data into a lower dimensional space. The natural division into three or four clusters on the dendro-grams from the MRI parameters did not reflect our 4 ex-perimental groups, due to the lack of differences between groups for T1, MTR and ADC. The natural division into four clusters on the dendograms from the mechanical properties reflected our 4 experimental groups. However, the differentiation between the in-situ and the digested 6h groups was not clear for the annulus fibrosus. The mech-anical properties were more able to classify the degener-ated IVDs than the MRI parameters.

Only 15 samples were considered per group. The power of all the significant statistical tests was over 0.8, justifying this number of samples. The quantification of the mechanical properties was limited to compression tests. The compression loading on the intervertebral disc in vivo is expected to result in large hydrostatic pres-sures within the nucleus pulposus. Thus the relation-ships established between the mechanical properties and MRI parameters are appropriated for the nucleus pulpo-sus. However, the highly oriented annulus fibrosus is submitted to more complicated deformation patterns. Shear is an important loading mode in the annulus fibrosus, particularly relevant under bending and torsion loading of the IVD. Future studies of the relationships between mechanical properties and MRI parameters within the annulus fibrosus should include shear tests as well as traction tests. Diffusion tensor imaging might be

the most relevant MRI technique to reflect the shear be-havior of the tissue.

Conclusions

Multi-parametric MRI is a sensitive and non-invasive technique for describing the alterations in mechanical properties of IVDs. This study showed that the compres-sive modulus and the permeability of isolated IVDs can be assessed mostly by magnetization transfer sequences and diffusion tensor imaging. However, the relationships have to be improved with the inclusion of MRI para-meters more sensitive to IVD degeneration such as T1ρ or CEST (Chemical Exchange Saturation Transfer). Be-fore the use of this technique to quantify the mechanical properties of IVDs in vivo on patients suffering from various diseases, the relationships have to be defined for each degeneration type of the tissue that mimics the pathology. Our MRI protocol associated to principal component analysis and agglomerative hierarchical clus-tering are promising tools to classify the degenerated intervertebral discs and further find biomarkers and pre-dictive factors of the evolution of the pathologies.

Competing interests

The authors declare that they have no competing interests, except GG who receives financial support (salary) from Philips Healthcare.

Authors’ contributions

MR carried out the experiments, all the data analysis, discussed the results and drafted the manuscript. DP proposed the design of the study, participated in the results discussion and helped to draft the manuscript. GG carried out the MRI experiments, participated to the data analysis and to the Figure 6 Dendograms generated from the principal components of the mechanical properties for the nucleus pulposus (a) and the annulus fibrosus (b). The Y axis is the distance between the two objects being connected and the X axis is the node number.

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results discussion, and corrected the manuscript. GB participated in the results discussion and corrected the manuscript. All authors read and approved the final manuscript.

Acknowledgment

The Natural Sciences and Engineering Research Council of Canada (NSERC, Discovery Grant), the Mechanical Engineering Department and the Research and Innovation Directorate, Ecole Polytechnique de Montréal (Canada), for the financial support.

Author details

1Mechanical Engineering Department, Ecole Polytechnique de Montréal,

Montréal, QC, Canada.2Research Center, CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada.3Philips Healthcare, Montréal, QC, Canada. 4

CHUM Saint-Luc, Université de Montréal, Montréal, QC, Canada.

Received: 1 February 2012 Accepted: 8 October 2012 Published: 12 October 2012

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doi:10.1186/1471-2474-13-195

Cite this article as: Recuerda et al.: Assessment of mechanical properties of isolated bovine intervertebral discs from multi-parametric magnetic resonance imaging. BMC Musculoskeletal Disorders 2012 13:195.

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Figure

Table 1 Trypsin digestion groups
Figure 1 Example of T1 weighted image (a), T2 weighted image (b), MT image with the off-resonance pulse (c), MT image without the off-resonance pulse (d) and Diffusion weighted image (e) for an isolated IVD.
Figure 2 Experimental setup to measure the axial permeability.
Table 2 Young ’ s modulus E (MPa), compressive modulus H A0 (MPa), permeabilities k r , k 0 and k a (e -15 m 4 /Ns) presented as mean ± SD for all groups (n=15 per group)
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